DE102022105336A1 - Method for determining optimized operating settings for drive train components of a commercial vehicle - Google Patents

Abstract

The invention relates to a method for determining optimized operating settings for drive train components of a commercial vehicle. The method includes the transmission (S20) of vehicle status data (5) of the commercial vehicle and vehicle environment data (6) resulting during a journey along a route (4) to a computing unit (7) external to the commercial vehicle. The method further comprises the use (S40) of the transmitted vehicle status data (5) and vehicle environment data (6) by the computing unit (7) to simulate the journey along the route (4) using a stored vehicle model (8) in order to obtain current operating settings (1). for drive train components (2) of the commercial vehicle (3). The method further includes carrying out (S60) further simulations of the journey along the route (4) by the computing unit (7) using the stored vehicle model (8) based on variations of the specific current operating settings (1) and determining (S80) optimized operating settings (1) for drive train components (2) of the commercial vehicle (3) based on an evaluation of the simulations carried out and the varied operating settings (1) with regard to definable target criteria. The optimized operating settings (1) are then transmitted (S100) to the commercial vehicle (3), for example by means of wireless data transmission (9) and/or during a visit to the workshop. The method according to the invention enables centralized optimization of operating settings for commercial vehicles that are already in practical use at the end customer.

Description

The invention relates to a method for determining optimized operating settings for drive train components of a commercial vehicle.

Operating settings for powertrain components of a commercial vehicle are determined as part of the development process of a commercial vehicle. Such operating settings can include, for example, operating settings for the control and/or regulation of powertrain systems and components, such as. B. appropriate operating settings for the combustion engine, switching on an electric motor, the cooling, the transmission and its switching application, or power distribution between the tractor unit and the semi-trailer/trailer in combinations, etc.

It is known from practice to optimize corresponding operating settings as part of vehicle development with the help of test drives. Here, vehicle condition data and vehicle environment data that arise during a test drive along a route are recorded and collected. The test drive is subsequently reproduced by development engineers based on the collected vehicle condition data and vehicle environment data using a computer-based vehicle model of the commercial vehicle as part of a simulation in order to determine and optimize the operating settings for the drive train components.

The disadvantage of this is that the operating settings determined in this way are optimal for the test route and the driving behavior during the test drive, but are not necessarily optimal for later actual use of the slot vehicle.

It is conceivable that a user actually uses the vehicle for different route profiles and/or under different environmental conditions than those used for the original optimization. Furthermore, it is conceivable that the driving behavior of the later driver differs greatly from the driving behavior that was used for the original optimization, e.g. B. was taken as a basis for the test drive. In addition, it is possible that different fleet operators of commercial vehicle fleets pursue different goals with their vehicle fleet and accordingly have different preferences and requirements with regard to the operating settings for powertrain components. For example, preferences and requirements may differ depending on the fleet operator in terms of the relative weighting of energy efficiency, average driving speed, tolerance of component wear and driving comfort, each of which would result in different optimized operating settings, e.g. B. to a different switching application of an automated transmission. Accordingly, an initial determination of the operating settings means that they cannot be optimal for different requirements.

It is therefore an object of the invention to provide an improved technique for determining optimized operating settings for drive train components of a commercial vehicle, with which disadvantages of conventional techniques can be avoided.

This task is solved by the method with the features of independent claim 1. Advantageous further developments are specified in the dependent claims and the description.

According to a general aspect of the invention, a method for determining optimized operating settings for powertrain components of a motor vehicle is provided. The motor vehicle is particularly preferably a commercial vehicle, for example a truck or bus. In other words, the vehicle can be a vehicle whose design and equipment are designed to transport people, transport goods or tow trailers. The vehicle is preferably a tractor unit, i.e. H. a vehicle for pulling a semi-trailer or trailer. The vehicle is particularly preferably a tractor unit without a coupled semi-trailer. The motor vehicle can be powered by an internal combustion engine. Alternatively or additionally, the motor vehicle can be driven by an electric motor, e.g. B. be battery-electric or fuel cell-based.

The method is preferably a computer-implemented method. The individual process steps can be carried out by different computing units (computers) that are in communication with one another. The method is described below using a highlighted exemplary embodiment of a commercial vehicle, wherein instead of the commercial vehicle described, the method can also be applied to a motor vehicle, at least with regard to the non-commercial vehicle-specific aspects.

The method includes the step of transmitting vehicle status that arises while driving along a route Data from the commercial vehicle (hereinafter also referred to as vehicle) and vehicle environment data to a computing unit external to the commercial vehicle.

The vehicle status data and vehicle environment data are determined by the commercial vehicle while driving and transmitted to the computing unit external to the commercial vehicle, e.g. B. transmitted wirelessly (“over-the-air”). Vehicle condition data is data that identifies and/or characterizes the condition of the vehicle during this journey and may include values for powertrain-specific operating parameters, which will be described below. The vehicle condition data can be used to understand the vehicle condition in detail during the journey, while the vehicle environment data indicates where and under what environmental conditions (outside temperature, etc.) the journey took place. The computing unit external to the commercial vehicle can be a computer (central computer) of the commercial vehicle manufacturer.

The method further includes the step of using the transmitted vehicle status data and vehicle environment data by the computing unit to simulate the journey along the route using a stored vehicle model in order to determine and/or evaluate current operating settings for drive train components of the commercial vehicle. In other words, based on relevant vehicle status data and environmental data (vehicle environment data), the current operating settings of the commercial vehicle, if not yet known, can be determined by means of a computer-aided simulation using a corresponding vehicle model stored in the computing unit. Furthermore, the current operating settings can be evaluated with regard to definable target criteria.

The method further includes the step of carrying out further simulations of the journey along the route by the computing unit using the stored vehicle model, based on variations of the specific current operating settings. This is followed by the step of determining optimized operating settings for drive train components of the commercial vehicle based on an evaluation of the simulations carried out with regard to definable target criteria. The evaluation of the simulations includes an evaluation of the varied operating settings, preferably also in comparison with one another and with the current operating settings, in order to select those operating settings that are optimal with regard to the target criteria. This step is also preferably carried out by the computing unit. In other words, based on the current operating settings, these are changed in order to carry out further simulations, which can then be evaluated in order to be able to determine optimal or at least improved operating settings for the commercial vehicle.

The method further includes the step of transmitting the optimized operating settings to the commercial vehicle. The transmission can take place, for example, by means of wireless data transmission. The transmission can take place directly to the commercial vehicle in operation or only during a visit to the workshop. The method steps according to the invention are preferably carried out for a commercial vehicle that is already in operation and/or operated by the end customer.

The method according to the invention enables centralized optimization of operating settings for commercial vehicles that are already in practical use at the end customer. This enables the use of powerful central computers outside the commercial vehicle to carry out and evaluate the simulations, preferably supported by machine learning methods, to determine the optimized operating settings. The combined knowledge (know-how) about the vehicle from the vehicle manufacturer can be advantageously incorporated here. Furthermore, data from other vehicles can also advantageously be incorporated into the analysis and determination of optimized operating settings. Operating settings made at the factory can advantageously be checked subsequently and optimized for vehicles already in use by the end customer based on vehicle condition and vehicle environmental data obtained in practical use.

Since the optimization of the operating settings takes place with regard to definable target criteria, the target criteria and thus the optimization can be defined (adjusted) flexibly with regard to the preferences of the end customer. A technical solution is therefore provided in order to be able to optimize a commercial vehicle automatically, in line with needs and adapted to the situation in terms of its operating settings for drive train components, even in later practical use.

• - eine Auswahl mehrerer Optionen für optimierte Betriebseinstellungen basierend auf unterschiedlichen Variationen der Betriebseinstellungen, wobei die Auswahl vorzugsweise automatisiert durch die Recheneinheit durchgeführt wird;
• - eine Bereitstellung von Informationen betreffend die ausgewählten mehreren Optionen zusammen mit einer Entscheidungsmöglichkeit an einen das Nutzfahrzeug betreibenden Flottenbetreiber zur Auswahl einer vom Flottenbetreiber präferierten Option für optimierte Betriebseinstellungen; und
• - das Empfangen der vom Flottenbetreiber mittels der Entscheidungsmöglichkeit ausgewählten präferierten Option zur Bestimmung der optimierten Betriebseinstellungen.

In an advantageous embodiment of the invention, the step of determining optimized operating settings for the drive train components of the commercial vehicle may include:

• - a selection of several options for optimized operating settings based on different variations of the operating settings, the selection preferably being carried out automatically by the computing unit;
• - a provision of information regarding the multiple options selected together with a decision option for a fleet operator operating the commercial vehicle to select an option for optimized operating settings preferred by the fleet operator; and
• - Receiving the preferred option selected by the fleet operator using the decision option to determine the optimized operating settings.

A technical solution is advantageously provided with which a fleet operator can be involved in optimizing the operational setting of one or more of his vehicles. The aforementioned provision of information about the multiple options and the receipt of the selected options can be supported and/or automated by a communication system for communication between a vehicle manufacturer and the fleet operator.

In a further preferred embodiment, the method further comprises the steps of identifying commercial vehicles within a fleet of commercial vehicles that have an identical or at least similar drive train configuration, and transmitting the optimized operating settings to the identified commercial vehicles in the fleet. The specific optimized operating settings can also advantageously be used to optimize the operating settings for further commercial vehicles in the fleet, in particular for commercial vehicles that are identical or similar in terms of their drive train configuration, without having to carry out separate simulation chains for each of the vehicles.

It was stated above that the determination of the optimized operating settings takes place with regard to definable target criteria. The definable target criteria can include at least one of the following target criteria: a travel time, energy and/or fuel consumption, operational wear of at least one component of the drive train, driving comfort, a range and an average speed of the commercial vehicle. Here, the target criteria are linked to at least one multi-criteria target function using a, preferably definable, weighting.

Such target criteria and multi-criteria target functions are known from the prior art. Here, the optimization of the operating settings of drive train components is understood as a multi-dimensional optimization problem that is described by a target function, which can include not only physical variables such as consumption, but also other requirements such as operational wear of components, etc.

According to an advantageous embodiment variant, the determination of the target criteria and/or their weighting or the selection of a target function from the at least one target function can be carried out by a user input and/or by querying from a database. A customer preference for determining the target criteria and/or their weighting and/or for selecting the target function can be stored in a corresponding database. The user input can be made using an appropriately designed website, an application program or, in general, a communication system that records the user input and transmits it to the computing unit for carrying out the simulations.

This embodiment variant offers the advantage that an end customer, in particular a fleet operator, can influence the optimization of the operating settings in a simple and transparent manner and change the specifications for this. For example, it is conceivable that a fleet operator notices that wear-related vehicle failures of certain drive train components are increasing. In response to this, the fleet operator could give greater weight to a corresponding target criterion that minimizes operational wear on the corresponding component of the drive train.

In a further embodiment, the above-described implementation of further simulations and the determination of the optimized operating settings are carried out using and/or supported by machine learning methods. These are preferably artificial intelligence, AI-based processes, e.g. B. using an artificial neural network. Such methods are particularly suitable for processing large amounts of data. The use of such methods also facilitates the application of the method for determining optimized operating settings for a large number of vehicles in the most automated possible way by processing large amounts of data, e.g. B. in the form of vehicle status data and vehicle environment data.

In one embodiment of the invention, further simulations can be carried out and the optimized operating settings can be determined for selected operating settings, which preferably correspond to at least one vehicle function. The selected operating settings and/or the at least one vehicle function are selected by user input and/or by querying from a database. In the database is preferred a customer preference is stored to determine the selection of operating settings and/or vehicle functions to be optimized. An advantage of this embodiment is that optimized operating settings are targeted for specific, e.g. B. vehicle function selectable by a customer can be carried out. By way of example only, such a vehicle function can be a cooling function or a cooling system of the drive train. In this case, only operating settings that affect the cooling function or the cooling system are optimized.

It was stated above that the vehicle condition data and vehicle environment data are used to simulate the journey along the route using a stored vehicle model. The vehicle model can include a longitudinal dynamics model to represent the vehicle's longitudinal dynamics and/or a thermodynamic powertrain model to represent thermal effects. Such vehicle models are vehicle-specific with regard to the special drive train configuration and are well known from the prior art in different versions and are therefore not described in more detail here. Vehicle manufacturers usually use such vehicle models to carry out corresponding simulations as part of vehicle development, as already mentioned at the beginning.

The vehicle surroundings data preferably includes location data and/or GPS data, i.e. H. Data about the current location and/or the current route, such as: B. Elevation/slope data of the route. The vehicle surroundings data can further include weather data, preferably weather data on the ambient temperature and/or wind speed, which occur while driving along the route. Weather data such as the ambient temperature influences, for example, the switching points for optimized fan switching and/or the optimal speed selection during a mountain journey with regard to the cooling performance of a powertrain cooling system. The more precisely the vehicle environment data is known, the more reliably the current operating settings can be simulated and then optimized.

In one embodiment, the operating settings can include a course, preferably a controlled or regulated course, of at least one state variable of at least one drive train component. The optimized operating settings include an optimal course with regard to the definable target criteria, preferably optimal control or regulation, of the at least one state variable.

The at least one state variable can include at least one of the following state variables: a speed selection of the vehicle, a gear selection, switching times and / or switching speeds for an automated transmission, a charge state of an energy storage device for providing electrical drive energy in a hybrid or electric drive train, a coolant temperature a primary or secondary cooling circuit of a drive train, switch-on and switch-off times of a fan for engine cooling and/or a pump of a primary or secondary cooling circuit of the drive train, switching times for a retarder, connection times of an electric auxiliary drive and a power distribution between a tractor unit and a semi-trailer and/or Trailer. The optimization of the operating settings for these state variables enables a particularly advantageous optimization of the drive train operation.

In one embodiment, the variation of the specific current operating settings includes a variation of operating parameters and/or state variables of the drive train components that can be set automatically within the framework of regulation and/or control processes. The corresponding regulation and/or control processes can thus be optimized. In this case, a state variable means a variable that describes the state of a drive train component. This can be, for example, a coolant temperature or a selected gear.

Alternatively or additionally, the variation of the specific current operating settings can include at least one of the following vehicle-related modification options: a tire diameter and a total weight, preferably a total train weight of a commercial vehicle designed as a tractor unit. For example, as part of the process optimization it can be recognized that different tires would be advantageous for the commercial vehicle, e.g. B. to improve fuel efficiency or reduce tire wear.

Alternatively or additionally, carrying out further simulations of the journey along the route may further include a variation of at least one of the following environmental parameters: an ambient temperature and road gradient. Both variations are parameters that cannot be influenced within the operating settings of a vehicle. However, these can influence the optimal setting of other operating settings of the drive train components, so that in this way e.g. B. improved operating settings of the vehicle depending on the ambient temperature ture and/or road gradient can be made.

According to a further aspect, the commercial vehicle described can be a tractor unit with a semi-trailer, wherein the vehicle data preferably includes load data of the semi-trailer. Preferably, the load data includes data on the weight and/or volume of the load. This allows for the fact that optimal operating settings can change depending on the load. For example, it may make sense to select a different gear when driving uphill for a heavily loaded vehicle than for a vehicle with a low load.

The previously described preferred embodiments and features of the invention can be combined with one another in any way. Further details and advantages of the invention are described below with reference to the accompanying drawings.

• 1 ein schematisches Ablaufdiagramm zur Illustration eines Verfahrens gemäß einer Ausführungsform der Erfindung;
• 2 ein schematisches Ablaufdiagramm zur Illustration eines Verfahrens gemäß einer weiteren Ausführungsform der Erfindung;
• 3 eine schematische Darstellung einer Datenkommunikation im Rahmen des Verfahrens gemäß einer Ausführungsform; und
• 4 eine schematische Darstellung einer Übermittlung von Fahrzeugzustandsdaten und Fahrzeugumfelddaten im Rahmen des Verfahrens gemäß einer Ausführungsform.

Show it:

• 1 a schematic flow diagram illustrating a method according to an embodiment of the invention;
• 2 a schematic flow diagram to illustrate a method according to a further embodiment of the invention;
• 3 a schematic representation of data communication as part of the method according to one embodiment; and
• 4 a schematic representation of a transmission of vehicle status data and vehicle environment data as part of the method according to one embodiment.

Identical or functionally equivalent elements are designated with the same reference numerals in all figures and some are not described separately.

1 shows a schematic flow diagram to illustrate a method for determining optimized operating settings for drive train components of a commercial vehicle according to an embodiment of the invention. In the following description of the process steps 1 (and the 2 ) is also referred to 3 and 4 .

The method includes the step S20 of recording and transmitting vehicle status data 5 of a commercial vehicle and vehicle surroundings data 6 resulting during a journey along a route to a computing unit external to the commercial vehicle. This vehicle status data 5 is data that identifies and/or characterizes the status of the vehicle during this journey. Here, values for drivetrain-specific operating parameters can be recorded, i.e. H. Operating data is collected from systems and components that are used to control or regulate powertrain components, e.g. B. Operating data of an internal combustion engine, an automated manual transmission and its switching application and/or an electric motor (depending on the vehicle's drive type), operating data on the cooling system of the drive train components, a retarder and a power distribution between the tractor unit and the semi-trailer/trailer. By way of example only, the vehicle status data 5 can include the recorded vehicle speed and, in the case of vehicles powered by internal combustion engines, the gear shift progression along the route, operating data for the cooling system of the drive train components, e.g. B. coolant temperatures, as well as data on the energy consumption of individual drive train components.

Such vehicle status data 5 can be collected by the commercial vehicle 3 along the route 4 in a manner known per se using the control devices and sensors installed in the commercial vehicle. Based on the determined vehicle status data, the vehicle status can be understood in detail while driving along the route 4.

The collected vehicle environment data 6 indicates where and under what environmental conditions (outside temperature, etc.) the journey along the route 4 took place. The vehicle surroundings data 6 preferably includes location data and/or GPS data, i.e. H. Data about the current location and/or the current route 4, such as. B. elevation/slope data or speed limits of the route 4. The vehicle environment data can also include weather data, preferably weather data on the ambient temperature, the season and/or wind speed that occur while driving along the route, or data resulting therefrom on the rolling resistance of the vehicle. The vehicle surroundings data on the route itself can be obtained from the vehicle navigation system, while surroundings data on the surroundings, such as weather data, can be queried from a weather database and/or recorded using the vehicle's corresponding surroundings sensors.

Which vehicle status data 5 and vehicle environment data 6 are recorded and transmitted depends, among other things, on the specific drive train configuration of the vehicle and also on which drive train component(s) 2 the operating settings are to be optimized, as well as the specific execution of the optimization calculation, ie which data is required for this.

The vehicle status data 5 and vehicle environment data 6 determined by the commercial vehicle 3 are determined wirelessly 9 to a computing unit 7 external to the commercial vehicle, e.g. B. by means of a data communication unit of the commercial vehicle 3, which is used for this purpose, for example. B. can use a mobile data connection. The computing unit external to the commercial vehicle can be a high-performance computer (central computer) 7 from the commercial vehicle manufacturer (cf. 3 ).

The computer 7 uses the transmitted vehicle status data 5 and vehicle environment data 6 to computer-aided the journey along the route based on a stored vehicle model 8, i.e. H. to be understood by simulation (step S40). Using this simulation, the current operating settings for the powertrain components of the commercial vehicle can be determined (if not already known). Furthermore, the current operating settings can be evaluated with regard to definable target criteria.

Subsequently, further simulations of the journey along the route are carried out by the computing unit based on the stored vehicle model (step S60). However, for these simulations the current operating settings are changed (varied). This is followed by step S80 of determining optimized operating settings for drive train components 2 of the commercial vehicle based on an evaluation of the simulations carried out with regard to definable target criteria.

The evaluation of the simulations includes an evaluation of the varied operating settings, preferably also in comparison with one another and with the current operating settings, in order to select those operating settings that are optimal with regard to the target criteria. This step is also carried out by the computing unit 7. In other words, based on the current operating settings, these are changed in order to carry out further simulations, which can then be evaluated in order to be able to determine optimal or at least improved operating settings for the commercial vehicle. The result can be, for example, changed limit temperatures for controlling components of the powertrain cooling system, or changed switching speeds for an automated manual transmission.

Depending on which operating settings, i.e. That is, for which component or subsystem of the drive train is to be determined and/or evaluated, it is advisable to use a vehicle (partial) model suitable for this purpose and the vehicle condition data and vehicle environment data required for this purpose. Merely as an example, a thermodynamic drive train model can be used in a manner known per se for the operating settings of the cooling system of the commercial vehicle to represent thermal effects as a vehicle model and data such as the temperature and pressure in the cooling circuit etc. can be used as vehicle condition data and this can be used as vehicle environment data. Environmental influencing parameters such as the ambient temperature are used.

It is advantageous to carry out the simulations and the determination of the optimized operating settings using and/or supported by machine learning methods. Due to the large amounts of data to be processed and complex models, it is advantageous to use artificial intelligence, AI-based methods using an artificial neural network.

For the simulations of steps S40 and S60 and the evaluation of the simulations in step S80, known vehicle models 8 can be used, which include a longitudinal dynamics model to represent the vehicle's longitudinal dynamics and a thermodynamic drive train model to represent thermal effects. The simulation of vehicle behavior using such models in the context of vehicle development is known from practice. Commercial software packages for multiphysics modeling of the drive train can also be used for this, such as: B. Matlab® and Simulink® from MathWorks and GT-SUITE® from Gamma Technologies. Such commercial software packages for vehicle development now also contain so-called artificial intelligence, AI modules that support corresponding AI-based simulations using vehicle models. The vehicle environment data and vehicle condition data that were obtained during test drives of the commercial vehicle as part of its development can initially be used as training data. Over time, however, the new vehicle status data and vehicle environment data that are continuously added through the application of the method can be used to continuously train the AI-based method and/or the artificial neural network used, etc. using this data.

For a possible implementation, reference is also made to the publication: “A multi-physical simulation model for the evaluation of drive and thermal management concepts in motor vehicles”, published by Christian Haupt, Technical University of Munich, as an example at: http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:91-diss-20130307-1114641-0-4. On the one hand, the publication describes a possible vehicle model for modeling the vehicle's longitudinal dynamics and for modeling the thermal processes of the drive train, which have a significant influence on fuel consumption. The publication further describes the determination of operating settings of powertrain components, supported by AI-based simulation and evaluation using artificial neural networks. The publication also gives examples of commercial software packages that are suitable for carrying out corresponding simulations for the operating settings of drive train components based on a vehicle model and for evaluating these on an AI-based basis. The execution of steps S40 to S80 can optionally be implemented based on the vehicle model of this publication and with the help of the simulations and software packages described there. The relevant Aspects of this publication are hereby incorporated by reference.

It was stated above that in step S80, optimized operating settings for drive train components of the commercial vehicle are determined based on an evaluation of the simulations carried out with regard to definable target criteria. The target criteria include several of the following target criteria: a driving time, energy and/or fuel consumption, operational wear of at least one component of the drive train and possibly further target criteria. The target criteria are linked to at least one multi-criteria target function using a definable weighting. The optimization of the operating settings of drive train components is understood as a multi-dimensional optimization problem that is described by such a target function. Here, partial cost functions corresponding to the individual target criteria are combined to form an overall cost function (quality functional) using summation.

Using this total cost function or the quality functional, the individual simulations, which are based on different operating settings, can now be evaluated. As a result, those varied operating settings can be obtained that are optimal. These can then be set as optimized operating settings. The target criteria, weightings of target criteria, and the multi-criteria target functions can be stored in the computing unit 7 or in a database 12, which the computing unit 7 can access. Furthermore, customer preferences for determining the target criteria and/or their weighting as well as preferences for selecting target functions and vehicle functions to be optimized can be stored in the database 12.

As part of steps S40 to S80, application processes in the vehicle that can be optimized as well as implausible or incorrect ones can be identified. These are, for example, short-term retarder activations, short fan activations, implausible switching or switching pendulums. Based on predetermined threshold values such as: B. Duration of connection or number of connections in a defined period of time can be determined that there is a condition that can be improved.

These optimized operating settings 1 can then be transmitted back to the commercial vehicle 3 (step S100) in order to adapt the operating settings there in accordance with the optimized operating settings. The transmission can take place directly wirelessly (“over-the-air”) to the commercial vehicle 3 in operation or only with a delay during a future visit to the workshop. Alternatively, there is also the possibility of transmitting the optimized operating settings to a fleet operator 10 of the commercial vehicle 3, who then transfers the optimized operating setting to the commercial vehicle 3.

2 shows a schematic flow diagram to illustrate a method according to a further embodiment of the invention.

A special feature of this embodiment variant is that an end customer of the commercial vehicle, in particular a fleet operator, can be included in the optimization of the operating settings.

According to this embodiment, the determination S80 of the optimized operating settings first includes selecting a plurality of options for optimized operating settings 1 in step S82 based on different variations of the operating settings.

The several options can e.g. B. can be provided in the form of different driving scenarios. The several driving scenarios can only include, by way of example, a first driving scenario (“consumption-optimized driving”), which of all driving scenarios has the highest level of energy consumption efficiency, e.g. B. fuel efficiency is optimized. This means that this first driving scenario corresponds to operating settings for drive train components that ensure the lowest possible energy consumption, e.g. B. fuel consumption of the commercial vehicle. The several driving scenarios can also, for. B. a second driving scenario (“time-optimized driving scenario”) drive") include that is most optimized for the shortest possible driving time and/or the highest possible average driving speed (and is less optimized for fuel efficiency). This means that this second driving scenario corresponds to operating settings that enable the fastest possible driving, even if this comes at the expense of fuel efficiency.

The options or driving scenarios can be selected, for example, by the computer 7, in which a different total cost function is used for each of the options or for each driving scenario to evaluate the simulations and varied operating settings. For the first driving scenario ("consumption-optimized driving"), energy consumption as a target criterion is particularly heavily weighted compared to other target criteria, while for the second driving scenario ("time-optimized driving"), a driving time as a target criterion is particularly heavily weighted compared to other target criteria.

In step S84, the information 11 relating to the selected several options, together with a decision option, can then be provided to a fleet operator 10 operating the commercial vehicle 3 to select an option for optimized operating settings 1 preferred by the fleet operator 10. They can then decide on one of the options and select this.

According to this embodiment, an operator of commercial vehicles can thus select a driving scenario that is advantageous for him or, in general, an option for optimized operating settings that is advantageous for him. The first driving scenario can be advantageous for a first fleet of vehicles whose operating costs should be as low as possible, while the second driving scenario can be advantageous for a second fleet of vehicles that is used for quick delivery of goods. Depending on the preferred option, determining the optimized operating settings results in a more fuel-optimized or time-optimized driving style of the commercial vehicle, e.g. B. through different switching applications in an automated transmission or different acceleration behavior in an operating mode with automated longitudinal guidance of the vehicle.

The preferred option for determining the optimized operating settings 1 selected by the fleet operator 10 using the decision option 11 can then be transmitted back to the computer 7 and received by it.

The provision of information regarding the selected several options together with a decision-making option to a fleet operator operating the commercial vehicle can take place via a website, an application program (“app”) or the like in order to inform the fleet operator about the selectable options. For this purpose, information about the options can be provided to explain them, e.g. E.g. how these differ in terms of fuel efficiency, average time savings per route, etc. The decision option can be realized in that one of the options can be selected by the fleet operator, e.g. B. can be clicked via a displayed selection menu. The result of this user input 13 is transmitted to the computing unit 7 in order to determine the optimized operating settings that are transmitted to the commercial vehicle based on the selected option.

On 2 A further embodiment variant is illustrated below using steps S102 and S104, which relates to step S100. The special feature of this embodiment variant is that the optimized operating settings determined are also used to update or optimize the operating settings for other commercial vehicles in the fleet, in particular for identical or similar commercial vehicles, without having to carry out separate simulation chains for each of the vehicles.

For this purpose, in step S102, commercial vehicles 3 are identified within a fleet of commercial vehicles that have an identical or at least similar drive train configuration. For example, based on the optimized operating setting or the resulting changed parameters, it can be checked to what extent the optimization can be transferred to vehicles with a similar configuration, e.g. B. because they are equipped with the same or a similar drivetrain configuration, where the changed parameters are also applicable. The optimized operating settings 1 are then transmitted S104 to the thus determined commercial vehicles 3 in the fleet. The transmission can be carried out as quickly as possible wirelessly “over the air” directly to the corresponding commercial vehicles or, if vehicles cannot be reached “over the air”, also with a time delay, as soon as a data connection is possible again or during the next visit to the workshop. When operating settings are changed that are classified as safety-critical, the fastest possible data transfer should generally be ensured.

It is possible that the optimized operating settings are first transmitted to the fleet operator and then the optimized ones Operating settings can be uploaded to the corresponding vehicles in his fleet. Accordingly, this technology enables a fleet operator to quickly optimize operating settings for entire parts of their vehicle fleet.

Although the invention has been described with reference to specific embodiments, it will be apparent to those skilled in the art that various changes may be made and equivalents substituted without departing from the scope of the invention. Even if the method was described in particular for the highlighted case of a commercial vehicle, the method is also generally applicable to determining the optimized operating setting of a motor vehicle and should be used in this regard. also considered revealed. Insofar as examples of fleet operators of commercial vehicles are described, these examples should also apply to operators of motor vehicle fleets. Accordingly, the invention is not intended to be limited to the embodiments disclosed, but is intended to include all embodiments that fall within the scope of the appended claims. In particular, the invention also claims protection for the subject matter and features of the subclaims, regardless of the claims referred to.

Reference symbol list

1

Optimized operating settings

2

Powertrain components

3

Commercial vehicle

4

Driving distance

5

Vehicle health data

6

Vehicle environment data

7

Computing unit external to the commercial vehicle

8th

Stored vehicle model

9

Wireless data transmission

10

Fleet operator

11

Information and decision-making ability

12

Database

13

User input

Claims (14)

Method, preferably computer-implemented method, for determining optimized operating settings (1) for drive train components (2) of a commercial vehicle (3), comprising the steps: a) transmission (S20) of vehicle status data (5) of the commercial vehicle and vehicle environment data (6) resulting during a journey along a route (4) to a computing unit (7) external to the commercial vehicle; b) Use (S40) of the transmitted vehicle status data (5) and vehicle environment data (6) by the computing unit (7) to simulate the journey along the route (4) using a stored vehicle model (8) in order to obtain current operating settings for drive train components (2). to determine the commercial vehicle (3); c) carrying out (S60) further simulations of the journey along the route (4) by the computing unit (7) using the stored vehicle model (8), based on variations of the specific current operating settings; d) Determination (S80) of optimized operating settings (1) for drive train components (2) of the commercial vehicle (3) based on an evaluation of the simulations carried out and the varied operating settings with regard to definable target criteria, and e) transmission (S100) of the optimized operating settings (1) to the commercial vehicle (3), for example by means of wireless data transmission (9) and/or during a visit to the workshop. Procedure according to Claim 1 , wherein the determination (S80) of the optimized operating settings comprises: a) selecting (S82) several options for optimized operating settings (1), for example in the form of several driving scenarios, based on different variations of the operating settings; b) Providing (S84) information (11) regarding the selected several options, together with a decision option (11), to a fleet operator (10) operating the commercial vehicle (3) for selecting an option for optimized operating settings (10) preferred by the fleet operator (10). 1), and c) receiving (S86) the preferred option selected by the fleet operator (10) using the decision option (11) for determining the optimized operating settings (1). Method according to one of the preceding claims, further comprising the steps: Determination (S102) of commercial vehicles (3) within a fleet of commercial vehicles that have an identical or at least similar drive train configuration, and Transmission (S104) of the optimized operating settings (1) to the identified commercial vehicles (3) in the fleet. Method according to one of the preceding claims, a) wherein the target criteria include at least one of the following target criteria: a travel time, a Energy and/or fuel consumption, operational wear of at least one component (2) of the drive train, driving comfort, a range and an average speed of the commercial vehicle (3), and b) the target criteria being determined by means of a, preferably definable, weighting to at least one multi-criteria Objective function can be linked. Procedure according to Claim 4 , further comprising the step: determining the target criteria and / or their weighting or selecting a target function from the at least one target function by a user input (13) and / or by querying from a database (11), in which preferably a customer preference for determining the target criteria and/or their weighting and/or for selecting the target function is stored. Method according to one of the preceding claims, wherein the implementation (S60) of further simulations and the determination (S80) of the optimized operating settings (1) by means of and/or supported by machine learning methods, preferably AI-based methods using an artificial neural network, he follows. Method according to one of the preceding claims, wherein the implementation (S60) of further simulations and the determination (S80) of the optimized operating settings (1) are carried out for selected operating settings (1) which correspond to at least one vehicle function, the at least one vehicle function being selected by a user input (13) and/or by querying from a database (12), in which a customer preference is preferably stored for determining the vehicle functions to be optimized. Method according to one of the preceding claims, wherein the vehicle model (8) comprises a longitudinal dynamics model for depicting the vehicle longitudinal dynamics and/or a thermodynamic drive train model for depicting thermal effects. Method according to one of the preceding claims, wherein the vehicle surroundings data (6) comprises: location data and/or GPS data, weather data, preferably weather data on the ambient temperature and/or wind speed for the route (4). Method according to one of the preceding claims, wherein the variation of the specific current operating settings (1) a) comprises a variation of operating parameters and/or state variables of the drive train components (2) that can be set automatically within the framework of regulation and/or control processes; and or b) a variation of at least one of the following vehicle-related modification options: a tire diameter and a total weight, preferably a total train weight of a commercial vehicle (3) designed as a tractor unit. Method according to one of the preceding claims, wherein carrying out (S60) further simulations further comprises: a variation of at least one of the following environmental parameters: an ambient temperature and road gradient. Method according to one of the preceding claims, wherein a) the operating settings (1) comprise a course, preferably a controlled or regulated course, of at least one state variable of at least one drive train component (2) for the route (4); and b) the optimized operating settings (1) have an optimal course with regard to the definable target criteria, preferably optimal control or regulation, which include at least one state variable. Procedure according to Claim 12 , wherein the at least one state variable comprises at least one of the following state variables: a) a speed selection of the vehicle (3); b) a gear selection, switching times and/or switching speeds for an automated transmission, c) a state of charge of an energy storage device for providing electrical drive energy in a hybrid or electric drive train, d) a coolant temperature of a primary or secondary cooling circuit of a drive train, e) switch-on and switch-off times a fan for engine cooling and/or a pump of a primary or secondary cooling circuit of the drive train, f) switching times for a retarder, g) switching times of an electric auxiliary drive h) a power distribution between a tractor unit and a semi-trailer and/or trailer. Method according to one of the preceding claims, wherein the commercial vehicle (3) is a tractor unit with a semi-trailer, the vehicle status data (5) preferably comprising load data of the semi-trailer, preferably data on the weight and/or volume of the load.

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